DNA methylation and human disease

iCancer-Pred: A tool for identifying cancer and its type using DNA methylation

DNA methylation is an important epigenetics, which occurs in the early stages of tumor formation. And it also is of great significance to find the relationship between DNA methylation and cancer. This paper proposes a novel model, iCancer-Pred, to identify cancer and classify its types further. The datasets of DNA methylation information of 7 cancer types have been collected from The Cancer Genome Atlas (TCGA). The coefficient of variation firstly is used to reduce the number of features, and then the elastic network is applied to select important features. Finally, a fully connected neural network is constructed with these selected features. In predicting seven types of cancers, iCancer-Pred has achieved an overall accuracy of over 97% accuracy with 5-fold cross-validation. For the convenience of the application, a user-friendly web server: http://bioinfo.jcu.edu.cn/cancer or http://121.36.221.79/cancer/ is available. And the source codes are freely available for download at https://github.com/Huerhu/iCancer-Pred.

Differentially hypomethylated cell-free DNA and coronary collateral circulation

BACKGROUND

The factors affecting cardioprotective collateral circulation are still incompletely understood. Recently, characteristics, such as CpG methylation of cell-free DNA (cfDNA), have been reported as markers with clinical utility. The aim of this study was to evaluate whether cfDNA methylation patterns are associated with the grade of coronary collateral circulation (CCC).

RESULT

In this case-control study, clinical and angiographic data were obtained from 143 patients (mean age, 58 years, male 71%) with chronic total coronary occlusion. Enzymatic methyl-sequencing (EM-seq) libraries were prepared using the cfDNA extracted from the plasma. Data were processed to obtain the average methylation fraction (AMF) tables of genomic regions from which blacklisted regions were removed. Unsupervised analysis of the obtained AMF values showed that some of the changes in methylation were due to CCC. Through random forest preparation process, 256 differentially methylated region (DMR) candidates showing strong association with CCC were selected. A random forest classifier was then constructed, and the area under the curve of the receiver operating characteristic curve indicated an appropriate predictive function for CCC. Finally, 20 DMRs were identified to have significantly different AMF values between the good and poor CCC groups. Particularly, the good CCC group exhibited hypomethylated DMRs. Pathway analysis revealed five pathways, including TGF-beta signaling, to be associated with good CCC.

CONCLUSION

These data have demonstrated that differential hypomethylation was identified in dozens of cfDNA regions in patients with good CCC. Our results support the clinical utility of noninvasively obtained epigenetic signatures for predicting collateral circulation in patients with vascular diseases.

PTEN-knockout regulates metabolic rewiring and epigenetic reprogramming in prostate cancer and chemoprevention by triterpenoid ursolic acid

PTEN (phosphatase and tensin homolog deleted on chromosome 10) is one of the most frequently mutated/deleted tumor suppressor genes in many human cancers. Ursolic acid (UA) is a natural triterpenoid possessing antioxidant, anti-inflammatory, and anticancer effects. However, how PTEN impacts metabolic rewiring and how UA modifies PTEN-driven metabolic and epigenetic reprogramming in prostate cancer (PCa) remains unknown. In the current study, we found that UA protects against PTEN knockout (KO)-induced tumorigenesis at different stages of PCa. Epigenomic CpG methyl-seq revealed UA attenuated PTEN KO-induced differentially methylated regions (DMRs) profiles. Transcriptomic RNA-seq showed UA abrogated PTEN KO-induced differentially expressed genes (DEGs) of PCa-related oncogenes' Has3, Cfh, and Msx1 overexpression, indicating UA plays a crucial role in PTEN KO-mediated gene regulation and its potential consequences on cancer interception. Association analysis of DEGs and DMRs identified that the mRNA expression of tumor suppressor gene BDH2, and oncogenes Ephas, Isg15, and Nos2 were correlated with the promoter CpG methylation status in the early-stage comparison groups indicating UA could regulate the oncogenes or tumor suppressor genes by modulating their promoter methylation at an early stage of prostate tumorigenesis. The metabolomic study showed UA attenuated PTEN KO-regulated cancer-associated metabolisms like purine metabolism/metabolites correlating with RNAseq findings, glycolysis/gluconeogenesis metabolism, as well as epigenetic-related metabolites pyruvate and lactate indicating UA plays a critical role in PTEN KO-mediated metabolic and epigenetic reprogramming and its consequences on cancer development. In this context, UA impacts metabolic rewiring causing epigenetic and transcriptomic reprogramming potentially contributing to the overall protection against prostate-specific PTEN KO-mediated PCa.

Ultrasensitive Simultaneous Detection of Multiple Rare Modified Nucleosides as Promising Biomarkers in Low-Put Breast Cancer DNA Samples for Clinical Multi-Dimensional Diagnosis

Early cancer diagnosis is essential for successful treatment and prognosis, and modified nucleosides have attracted widespread attention as a promising group of cancer biomarkers. However, analyzing these modified nucleosides with an extremely low abundance is a great challenge, especially analyzing multiple modified nucleosides with a different abundance simultaneously. In this work, an ultrasensitive quantification method based on chemical labeling, coupled with LC-MS/MS analysis, was established for the simultaneous quantification of 5hmdC, 5fdC, 5hmdU and 5fdU. Additionally, the contents of 5mdC and canonical nucleosides could be obtained at the same time. Upon derivatization, the detection sensitivities of 5hmdC, 5fdC, 5hmdU and 5fdU were dramatically enhanced by several hundred times. The established method was further applied to the simultaneous detection of nine nucleosides with different abundances in about 2 μg genomic DNA of breast tissues from 20 breast cancer patients. The DNA consumption was less than other overall reported quantification methods, thereby providing an opportunity to monitor rare, modified nucleosides in precious samples and biology processes that could not be investigated before. The contents of 5hmdC, 5hmdU and 5fdU in tumor tissues and normal tissues adjacent to the tumor were significantly changed, indicating that these three modified nucleosides may play certain roles in the formation and development of tumors and be potential cancer biomarkers. While the detection rates of 5hmdC, 5hmdU and 5fdU alone as a biomarker for breast cancer samples were 95%, 75% and 85%, respectively, by detecting these three cancer biomarkers simultaneously, two of the three were 100% consistent with the overall trend. Therefore, simultaneous detection of multiple cancer biomarkers in clinical samples greatly improved the accuracy of cancer diagnosis, indicating that our method has great application potential in clinical multidimensional diagnosis.

Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI

BACKGROUND

DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing.

RESULTS

We propose a comprehensive approach of combined DNA methylation datasets to classify controls and patients. The solution includes data harmonization, construction of machine learning classification models, dimensionality reduction of models, imputation of missing values, and explanation of model predictions by explainable artificial intelligence (XAI) algorithms. We show that harmonization can improve classification accuracy by up to 20% when preprocessing methods of the training and test datasets are different. The best accuracy results were obtained with tree ensembles, reaching above 95% for Parkinson's disease. Dimensionality reduction can substantially decrease the number of features, without detriment to the classification accuracy. The best imputation methods achieve almost the same classification accuracy for data with missing values as for the original data. XAI approaches have allowed us to explain model predictions from both populational and individual perspectives.

CONCLUSIONS

We propose a methodologically valid and comprehensive approach to the classification of healthy individuals and patients with various diseases based on whole-blood DNA methylation data using Parkinson's disease and schizophrenia as examples. The proposed algorithm works better for the former pathology, characterized by a complex set of symptoms. It allows to solve data harmonization problems for meta-analysis of many different datasets, impute missing values, and build classification models of small dimensionality.

Deciphering the role of aberrant DNA methylation in NAFLD and NASH

The global incidence of nonalcoholic fatty liver disease (NAFLD) is mounting incessantly, and it is emerging as the most frequent cause of chronic and end stage liver disorders. It is the starting point for a range of conditions from simple steatosis to more progressive nonalcoholic steatohepatitis (NASH) and associated hepatocellular carcinoma (HCC). Dysregulation of insulin secretion and dyslipidemia due to obesity and other lifestyle variables are the primary contributors to establishment of NAFLD. Onset and progression of NAFLD is orchestrated by an interplay of metabolic environment with genetic and epigenetic factors. An incompletely understood mechanism of NAFLD progression has greatly hampered the progress in identification of novel prognostic and therapeutic strategies. Emerging evidence suggests altered DNA methylation pattern as a key determinant of NAFLD pathogenesis. Environmental and lifestyle factors can manipulate DNA methylation patterns in a reversible manner, which manifests as changes in gene expression. In this review we attempt to highlight the importance of DNA methylation in establishment and progression of NAFLD. Development of novel diagnostic, prognostic and therapeutic strategies centered around DNA methylation signatures and modifiers has also been explored.

HLA-C dysregulation as a possible mechanism of immune evasion in SARS-CoV-2 and other RNA-virus infections

One of the mechanisms by which viruses can evade the host’s immune system is to modify the host’s DNA methylation pattern. This work aims to investigate the DNA methylation and gene expression profile of COVID-19 patients, divided into symptomatic and asymptomatic, and healthy controls, focusing on genes involved in the immune response. In this study, changes in the methylome of COVID-19 patients’ upper airways cells, the first barrier against respiratory infections and the first cells presenting viral antigens, are shown for the first time. Our results showed alterations in the methylation pattern of genes encoding proteins implicated in the response against pathogens, in particular the HLA-C gene, also important for the T-cell mediated memory response. HLA-C expression significantly decreases in COVID-19 patients, especially in those with a more severe prognosis and without other possibly confounding co-morbidities. Moreover, our bionformatic analysis revealed that the identified methylation alteration overlaps with enhancers regulating HLA-C expression, suggesting an additional mechanism exploited by SARS-CoV-2 to inhibit this fundamental player in the host’s immune response. HLA-C could therefore represent both a prognostic marker and an excellent therapeutic target, also suggesting a preventive intervention that conjugate a virus-specific antigenic stimulation with an adjuvant increasing the T-cell mediated memory response.

Implication of the Mediterranean diet on the human epigenome

Epigenetics, defined as "hereditary changes in gene expression that occur without any change in the DNA sequence", consists of various epigenetic marks, including DNA methylation, histone modifications, and non-coding RNAs. The epigenome, which has a dynamic structure in response to intracellular and extracellular stimuli, has a key role in the control of gene activity, since it is located at the intersection of cellular information encoded in the genome and molecular/chemical information of extracellular origin. The focus shift of studies to epigenetic reprogramming has led to the formation and progressive importance of a concept called "nutriepigenetics", whose aim is to prevent diseases by intervening on nutrition style. Among the diet types adopted in the world, the renowned Mediterranean Diet (MD), being rich in unsaturated fatty acids and containing high levels of whole grain foods and large quantities of fruits, vegetables, and legumes, has shown numerous advantages in excluding chronic diseases. Additionally, the fact that this diet is rich in polyphenols with high antioxidant and anti-inflammatory properties has an undeniable effect in turning some cellular pathways against the disease. It is also apparent that the effects of polyphenols on the epigenome cause changes in mechanisms such as DNA methylation and histone acetylation/deacetylation, which have a regulatory effect on gene regulation. This review presents the effects of long-term consumption of nutrients from the MD on the epigenome and discusses the benefits of this diet in the treatment and even prevention of chronic diseases.

Hypertension Related to Obesity: Pathogenesis, Characteristics and Factors for Control

The World Health Organization (WHO) refers to obesity as abnormal or excessive fat accumulation that presents a health risk. Obesity was first designated as a disease in 2012 and since then the cost and the burden of the disease have witnessed a worrisome increase. Obesity and hypertension are closely interrelated as abdominal obesity interferes with the endocrine and immune systems and carries a greater risk for insulin resistance, diabetes, hypertension, and cardiovascular disease. Many factors are at the interplay between obesity and hypertension. They include hemodynamic alterations, oxidative stress, renal injury, hyperinsulinemia, and insulin resistance, sleep apnea syndrome and the leptin-melanocortin pathway. Genetics, epigenetics, and mitochondrial factors also play a major role. The measurement of blood pressure in obese patients requires an adapted cuff and the search for other secondary causes is necessary at higher thresholds than the general population. Lifestyle modifications such as diet and exercise are often not enough to control obesity, and so far, bariatric surgery constitutes the most reliable method to achieve weight loss. Nonetheless, the emergence of new agents such as Semaglutide and Tirzepatide offers promising alternatives. Finally, several molecular pathways are actively being explored, and they should significantly extend the treatment options available.

Whole-genome long-read TAPS deciphers DNA methylation patterns at base resolution using PacBio SMRT sequencing technology

Long-read sequencing provides valuable information on difficult-to-map genomic regions, which can complement short-read sequencing to improve genome assembly, yet limited methods are available to accurately detect DNA methylation over long distances at a whole-genome scale. By combining our recently developed TET-assisted pyridine borane sequencing (TAPS) method, which enables direct detection of 5-methylcytosine and 5-hydroxymethylcytosine, with PacBio single-molecule real-time sequencing, we present here whole-genome long-read TAPS (wglrTAPS). To evaluate the performance of wglrTAPS, we applied it to mouse embryonic stem cells as a proof of concept, and an N50 read length of 3.5 kb is achieved. By sequencing wglrTAPS to 8.2× depth, we discovered a significant proportion of CpG sites that were not covered in previous 27.5× short-read TAPS. Our results demonstrate that wglrTAPS facilitates methylation profiling on problematic genomic regions with repetitive elements or structural variations, and also in an allelic manner, all of which are extremely difficult for short-read sequencing methods to resolve. This method therefore enhances applications of third-generation sequencing technologies for DNA epigenetics.

Identification of Melanoma Subsets Based on DNA Methylation Sites and Construction of a Prognosis Evaluation Model

Background

Melanoma is a lethal skin malignant tumor, and its formation or development is regulated by various genetic and epigenetic molecules. Although there are traditional methods provided for the doctors to evaluate the patients' prognosis or make the diagnosis, the novel method based on epigenetic markers is still needed to make the early diagnosis.

Results

We identified 256 melanoma-independent prognosis-related methylation sites (P < 0.0001) and divided patients into seven methylation subgroups. Methylation levels and survival time in the C2 subgroup were lower than that of other clusters (P < 0.05). We established the predicted model of prognosis risk for melanoma using the significantly changed methylation sites in C2. The model efficiently divided patients into high- and low-risk groups (area under the receiver operating characteristic curve, 0.833). Risk scores and patient survival time were negatively correlated (r_s = −0.325, P < 0.0001). Genes corresponding to the independent prognosis-associated methylation sites were enriched in cancer- and immunology-related pathways. We identified 35 hub genes. DOK2, GBP4, PSMB9, and NLRC5 were significantly changed according to methylation subgroups, survival, tumor stages, and T categories and were positively correlated, which was validated in the testing group (P < 0.05). The levels of DOK2, GBP4, PSMB9, and NLRC5 had an opposite trend to their methylation sites in patients with poor prognosis.

Conclusions

We identified seven DNA methylation subtypes and constructed a highly effective prognosis risk assessment model. The transcript levels of key genes corresponding to the independent prognosis-related methylation sites were significantly changed in patients according to prognosis and positively correlated with each other, indicating they may collaboratively promote melanoma formation. These findings further our understanding of the mechanism of melanoma and provide new targets for diagnosis and treatment.

Comprehensive Analysis of GDF10 Methylation Site-Associated Genes as Prognostic Markers for Endometrial Cancer

Growth differentiation factor-10 (GDF10) with its methylation trait has recently been found to play a crucial regulatory and communication role in cancers. This investigation aims to identify GDF10 methylation site-associated genes that are closely associated with endometrial cancer (EC) patients' survival based on normal and UCEC samples from the UCSC Xena database. Our study revealed for the first time that EC exhibited significantly higher levels of GDF10 promoter methylation in comparison with normal tissues. Multiple differentiated methylation sites, which have prognostic value due to their apparent survival differences, were found in the GDF10 promoter region. We performed weighted gene coexpression network analysis (WGCNA) on EC tissues and paraneoplastic tissues while using these differentially methylated sites as phenotypes for selecting the most correlated key modules and their internal genes. To obtain a gene set, the key module genes and differentially expressed genes (DEGs) of EC were intersected. The least absolute shrinkage and selection operator (LASSO) regression along with multivariate Cox regression were performed from the gene set and we screened out the key genes B4GALNT3, DNAJC22, and GREB1. Finally, a prognostic model was validated for effectiveness based on these genes. Additionally, Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) were applied to assess and verify the model, and they showed good prognosis prediction. Moreover, the differences in risk scores were statistically significant with age, tumor stage, and grade. They may be related to the immune infiltration of tumors as well. In conclusion, based on the methylation-related genes associated with GDF10, we developed a prognosis model for EC patients. It might provide a fresh view for further research and treatment of EC.

Identification of novel genetic and epigenetic regulators of different tissue types of cervical cancer

OBJECTIVES

The study aimed to find differential gene mutations, DNA methylation, and expression profiles among different categories of cervical cancer samples.

METHODS

The study was based on freely available gene mutations, promoter methylation, and gene expression status of The Cancer Genome Atlas (TCGA) cervical cancer samples and adjacent normal tissues in the Genomic Data Commons (GDC) portal. The association of CpG island methylation with gene expression was determined through negative correlation analysis.

RESULTS

We identified that the ErbB signaling pathway and proteoglycans pathway was significantly associated with adenocarcinoma cervical cancers patients. In these pathways, missense mutation especially S310F in the ERBB2 gene as well as G12D and A146T in the KRAS gene were significantly associated with adenocarcinoma cases. Furthermore, a comparison of SCC cases with adjacent control tissues revealed differential hypermethylation of two CpG positions of the KAAG1 gene and differential downregulation of NPY1R and NPY5R genes in cervical squamous cell carcinoma compared to cervical adenocarcinoma cases and adjacent normal tissues. Specifically, the hypermethylation of the promoter region of the KAAG1 gene might be responsible for the carcinogenesis of cervical squamous cells exclusively and methylation marks can be reversible by the widely used drug, azacytidine. In contrast, adenocarcinoma cervical cancer cases may be treated with floxuridine which is successfully utilized for other tissue-specific adenocarcinoma cases.

CONCLUSIONS

These results provide valuable insight into the differential molecular markers among the categories of cervical cancer, which helps our ability to classify these cancers and for targeted therapy.

Spatiotemporal specificity of correlated DNA methylation and gene expression pairs across different human tissues and stages of brain development

DNA methylation (DNAm) that occurs on promoter regions is primarily considered to repress gene expression. Previous studies indicated that DNAm could also show positive correlations with gene expression. Both DNAm and gene expression profiles are known to be tissue- and development-specific. This study aims to investigate how DNAm and gene expression are coordinated across different human tissues and developmental stages, as well as the biological significance of such correlations. By analyzing 2,239 samples with both DNAm and gene expression data in the same human subjects obtained from six published datasets, we evaluated the correlations between gene and CpG pairs (GCPs) at cis-regions and compared significantly correlated GCPs (cGCPs) across different tissues and brains at different age groups. A total of 37,363 cGCPs was identified in the six datasets; approximately 38% of the cGCPs were positively correlated. The majority (>90%) of cGCPs was tissue- or development-specific. We also observed that the correlation direction can be opposite in different tissues and ages. Further analysis highlights the importance of cGCPs for their cellular functions and potential roles in complex traits and human diseases. For instance, the early developmental brain possessed a highly unique set of cGCPs that were associated with neurogenesis and psychiatric disorders. By assessing the epigenetic factors involved in cGCPs, we discovered novel regulatory mechanisms of positive cGCPs distinct from negative cGCPs, which were related to multiple factors, such as H3K27me3, CTCF, and JARD2. The catalogue of cGCPs compiled can be used to guide functional interpretation of genetic and epigenetic studies.

Epigenomic effects of vitamin D in colorectal cancer

Vitamin D regulates a plethora of physiological processes in the human body and has been proposed to exert several anticancer effects. Epigenetics plays an important role in regulating vitamin D actions. In this review, we highlight the recent advances in the understanding of different epigenetic factors such as lncRNAs, miRNAs, methylation and acetylation influenced by vitamin D and its downstream targets in colorectal cancer to find more potential therapeutic targets. We discuss how vitamin D exerts anticancer properties through interactions between the vitamin D receptor and genes (e.g., SLC30A10), the microenvironment, microbiota and other factors in colorectal cancer. Developing therapeutic approaches targeting the vitamin D signaling system will be aided by a better knowledge of the epigenetic impact of vitamin D.

Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis

Background

Aberrant DNA methylation patterns are of increasing interest in the study of psoriasis mechanisms. This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily explore its molecular mechanisms.

Methods

GSE13355, GSE14905, and GSE73894 were collected from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated region- (DMR-) genes between psoriasis and control samples were combined to obtain differentially expressed methylated genes. Subsequently, a protein-protein interaction (PPI) network was established to analyze the interaction between differentially expressed methylated genes. Moreover, the hub genes of psoriasis were screened by the least absolute shrinkage and selection operator (LASSO), Random Forest (RF), and Support Vector Machine (SVM), which were further performed single-gene gene set enrichment analysis (GSEA) to clarify the pathogenesis of psoriasis. The druggable genes were predicted using DGIdb. Finally, the expressions of hub genes in psoriasis lesions and healthy controls were detected by immunohistochemistry (IHC) and quantitative real-time PCR (RT-qPCR).

Results

In this study, a total of 767 DEGs and 896 DMR-genes were obtained. Functional enrichment showed that they were significantly associated with skin development, skin barrier function, immune/inflammatory response, and cell cycle. The combined transcriptomic and DNA methylation data resulted in 33 differentially expressed methylated genes, of which GJB2 was the final identified hub gene for psoriasis, with robust diagnostic power. IHC and RT-qPCR showed that GJB2 was significantly higher in psoriasis samples than those in healthy controls. Additionally, GJB2 may be involved in the development and progression of psoriasis by disrupting the body's immune system, mediating the cell cycle, and destroying the skin barrier, in addition to possibly inducing diseases related to the skeletal aspects of psoriasis. Moreover, OCTANOL and CARBENOXOLONE were identified as promising compounds through the DGIdb database.

Conclusion

The abnormal expression of GJB2 might play a critical role in psoriasis development and progression. The genes identified in our study might serve as a diagnostic indicator and therapeutic target in psoriasis.

DNA Methylation Expression Profile of Blood Heat Syndrome and Blood Stasis Syndrome in TCM Psoriasis

Objective

Traditional Chinese medicine (TCM) emphasizes treatment based on syndrome differentiation. This study aimed to clarify the characteristics of DNA methylation expression profiles in peripheral blood mononuclear cells (PBMCs) in patients with psoriasis and analyze the differences in these profiles among different TCM syndromes of psoriasis in order to provide a material basis for the diversity of these syndromes.

Methods

Blood samples were collected from 32 participants, including 14 patients with psoriatic blood heat syndrome (BHS), 12 patients with psoriatic blood stasis syndrome (BSS), and 6 healthy controls. PBMCs were extracted and subjected to DNA quality inspection. An Illumina Human Methylation 850k chip was used to sequence each group of samples. According to gene annotation classification together with CpG island annotation classification, the differentially methylated regions between sample groups were screened, while Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were applied to perform functional analyses of DMGs. Finally, the DMGs closely correlating with psoriatic severity were screened using Spearman's correlation analysis.

Results

Compared with normal controls, patients with psoriasis showed an overall trend of hypermethylation. In psoriasis, the differential methylation probes were mainly distributed on gene body region on the genome, while those in CpG regions were mainly distributed in CpG islands. Compared with healthy controls, the overall trends in methylation were similar in psoriatic BHS and BSS patients compared to healthy controls. However, bioinformatic analysis revealed different functions of DMGs. We also found that the methylation levels of TRIM14 and PRDM16 were closely correlated with PASI scores and could serve as potential biomarkers to assess the severity of psoriasis.

Conclusions

Our study, for the first time, indicated the possible involvement of DNA methylation in regulating the characteristics of TCM syndromes of psoriasis, providing a new direction for research into TCM psoriatic syndromes.

msPIPE: a pipeline for the analysis and visualization of whole-genome bisulfite sequencing data

BACKGROUND

DNA methylation is an important epigenetic modification that is known to regulate gene expression. Whole-genome bisulfite sequencing (WGBS) is a powerful method for studying cytosine methylation in a whole genome. However, it is difficult to obtain methylation profiles using the WGBS raw reads and is necessary to be proficient in all types of bioinformatic tools for the study of DNA methylation. In addition, recent end-to-end pipelines for DNA methylation analyses are not sufficient for addressing those difficulties.

RESULTS

Here we present msPIPE, a pipeline for DNA methylation analyses with WGBS data seamlessly connecting all the required tasks ranging from data pre-processing to multiple downstream DNA methylation analyses. The msPIPE can generate various methylation profiles to analyze methylation patterns in the given sample, including statistical summaries and methylation levels. Also, the methylation levels in the functional regions of a genome are computed with proper annotation. The results of methylation profiles, hypomethylation, and differential methylation analysis are plotted in publication-quality figures. The msPIPE can be easily and conveniently used with a Docker image, which includes all dependent packages and software related to DNA methylation analyses.

CONCLUSION

msPIPE is a new end-to-end pipeline designed for methylation calling, profiling, and various types of downstream DNA methylation analyses, leading to the creation of publication-quality figures. msPIPE allows researchers to process and analyze the WGBS data in an easy and convenient way. It is available at https://github.com/jkimlab/msPIPE and https://hub.docker.com/r/jkimlab/mspipe .

Epigenetic Dysregulations in Arsenic-Induced Carcinogenesis

Arsenic is a crucial environmental metalloid whose high toxicity levels negatively impact human health. It poses significant health concerns to millions of people in developed and developing countries such as the USA, Canada, Bangladesh, India, China, and Mexico by enhancing sensitivity to various types of diseases, including cancers. However, how arsenic causes changes in gene expression that results in heinous conditions remains elusive. One of the proposed essential mechanisms that still has seen limited research with regard to causing disease upon arsenic exposure is the dysregulation of epigenetic components. In this review, we have extensively summarized current discoveries in arsenic-induced epigenetic modifications in carcinogenesis and angiogenesis. Importantly, we highlight the possible mechanisms underlying epigenetic reprogramming through arsenic exposure that cause changes in cell signaling and dysfunctions of different epigenetic elements.

Epigenetics and environment in breast cancer: New paradigms for anti-cancer therapies

Breast cancer remains the most frequently diagnosed cancer in women worldwide. Delayed presentation of the disease, late stage at diagnosis, limited therapeutic options, metastasis, and relapse are the major factors contributing to breast cancer mortality. The development and progression of breast cancer is a complex and multi-step process that incorporates an accumulation of several genetic and epigenetic alterations. External environmental factors and internal cellular microenvironmental cues influence the occurrence of these alterations that drives tumorigenesis. Here, we discuss state-of-the-art information on the epigenetics of breast cancer and how environmental risk factors orchestrate major epigenetic events, emphasizing the necessity for a multidisciplinary approach toward a better understanding of the gene-environment interactions implicated in breast cancer. Since epigenetic modifications are reversible and are susceptible to extrinsic and intrinsic stimuli, they offer potential avenues that can be targeted for designing robust breast cancer therapies.

KCNJ14 knockdown significantly inhibited the proliferation and migration of colorectal cells

Background

This study attempted to verify the potential of KCNJ14 as a biomarker in colorectal cancer (CRC).

Methods

Data on transcriptomics and DNA methylation and the clinical information of CRC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Biological information analysis methods were conducted to determine the role of KCNJ14 in the prognosis, diagnosis, immune cell infiltration, and regulation mechanism of CRC patients. The effect of KCNJ14 on the proliferation and migration of HCT116 and SW480 CRC cell lines was verified by in vitro experiments (MTT, colony-forming, wound healing, and transwell assays). Western blotting was performed to detect the effect of KCNJ14 on the levels of mTOR signalling pathway-related proteins.

Results

KCNJ14 expression was remarkably increased in CRC tissues and cell lines, which reduced the overall survival time of patients. KCNJ14 mRNA was negatively regulated by its methylation site cg17660703, which can also endanger the prognosis of patients with CRC. Functional enrichment analysis suggested that KCNJ14 is involved in the mTOR, NOD-like receptor, and VEGF signalling pathways. KCNJ14 expression was positively correlated with the number of CD4 + T cells and negatively correlated with that of CD8 + T cells in the immune microenvironment. KCNJ14 knockdown significantly reduced not only the proliferation and migration of CRC cell lines but also the levels of mTOR signalling pathway-related proteins.

Conclusions

This study not only increases the molecular understanding of KCNJ14 but also provides a potentially valuable biological target for the treatment of colorectal cancer.

A Novel Prognosis Signature Based on Ferroptosis-Related Gene DNA Methylation Data for Lung Squamous Cell Carcinoma

Ferroptosis-related genes regulating an iron- and lipid reactive oxygen species (ROS)-dependent form of programmed cell death suggest critical roles for ferroptosis in cancers. However, the prognostic value of ferroptosis-related epigenetic features such as DNA methylation in lung squamous cell carcinoma (LUSC) needs to be studied. Ferroptosis-related genes are collected from the FerrDb database, and the methylation data of these related genes in LUSC methylation data downloaded from the TCGA are retrieved. The DNA methylation data (362 LUSC samples) were analyzed to screen prognostic ferroptosis-related methylation sites. After patients with complete overall survival (OS) information were randomly separated into training cohort (n = 200) and validation cohort (n = 162), the least absolute shrinkage and selection operator (LASSO) and the Cox regression were used to establish and validate the prognostic signature. The time-dependent receiver operating characteristic (ROC) and Kaplan–Meier survival curve analyses, Harrell's concordance index (C-index), calibration analysis, and decision curve analysis (DCA) were performed to evaluate the risk signature and related nomogram. A series of other bioinformatics approaches such as mexpress, cbioportal, maftools, string, metascape, TIMER, and Kaplan–Meier survival curve analysis were also used to determine the methylation, mutation status, protein interaction network or functional enrichment, effects on immune cell infiltration, or expression level prognosis of those signature-related genes. A total of 137 DNA methylation sites were identified as prognostic predictors corresponding to 109 ferroptosis-related genes (FRGs). The methylation signature containing 31 methylation sites proved to be superior predictive efficiency in predicting the 1-, 3-, 5-, and 10-year OS. 8 out of 28 signature-related genes were significantly related to OS time or OS state in patients with LUSC. In addition, DUSP1, ZFN36, and ALOX5 methylation status also correlated with pathological M and ALOX5 methylation correlated with pathological N. The prognostic prediction efficiency of T, N, M, and the stage was inferior to that of the DNA methylation signature. LUSC patients in the high-risk group own a significantly larger number of variants of FRGs than those in the low-risk group. In addition, negative or positive correlation patterns were presented among the different infiltrating immune cells with risk scores or signature-related genes in patients with LUSC. The expression level of 15 signature-related genes showed a significant relationship with OS of LUSC patients. A novel prognostic nomogram survival model containing 4 factors including age, pathologic T, stage, and risk group was constructed and validated, AndC-index, decision curve analysis (DCA), and calibration analysis demonstrated its excellent predictive performance. The FRG DNA methylation data-based prognostic model acts as a powerful prognostic prediction indicator in LUSC patients and is advantageous over the traditional model based on T, N, M, and stage.

The Role of DNA Methylation in Stroke Recovery

Epigenetic alterations affect the onset of ischemic stroke, brain injury after stroke, and mechanisms of poststroke recovery. In particular, DNA methylation can be dynamically altered by maintaining normal brain function or inducing abnormal brain damage. DNA methylation is regulated by DNA methyltransferase (DNMT), which promotes methylation, DNA demethylase, which removes methyl groups, and methyl-cytosine–phosphate–guanine-binding domain (MBD) protein, which binds methylated DNA and inhibits gene expression. Investigating the effects of modulating DNMT, TET, and MBD protein expression on neuronal cell death and neurorepair in ischemic stroke and elucidating the underlying mechanisms can facilitate the formulation of therapeutic strategies for neuroprotection and promotion of neuronal recovery after stroke. In this review, we summarize the role of DNA methylation in neuroprotection and neuronal recovery after stroke according to the current knowledge regarding the effects of DNA methylation on excitotoxicity, oxidative stress, apoptosis, neuroinflammation, and recovery after ischemic stroke. This review of the literature regarding the role of DNA methylation in neuroprotection and functional recovery after stroke may contribute to the development and application of novel therapeutic strategies for stroke.

CDH1 (E-cadherin) Gene Methylation in Human Breast Cancer: Critical Appraisal of a Long and Twisted Story

Simple Summary

Genes can be inactivated by specific modifications of DNA bases, most often by adding a methyl group to the DNA base cytosine if it is followed by guanosine (CG methylation). This modification prevents gene expression and has been reported for many different genes in nearly all types of cancer. A prominent example is the gene CDH1, which encodes the cell-adhesion molecule E-cadherin. This is an important player in the spreading of tumor cells within the body (metastasis). Particularly in human breast cancer, many different research groups have studied the inactivation of the CDH1 gene via DNA methylation using various methods. Over the last 20 years, different, in part, even contradicting results have been published for the CDH1 gene in breast cancer. This review summarizes the most important publications and explains the bewildering heterogeneity of results through careful analysis of the methods which have been used.

Abstract

Epigenetic inactivation of a tumor suppressor gene by aberrant DNA methylation is a well-established defect in human tumor cells, complementing genetic inactivation by mutation (germline or somatic). In human breast cancer, aberrant gene methylation has diagnostic, prognostic, and predictive potential. A prominent example is the hypermethylation of the CDH1 gene, encoding the adhesion protein E-Cadherin (“epithelial cadherin”). In numerous publications, it is reported as frequently affected by gene methylation in human breast cancer. However, over more than two decades of research, contradictory results concerning CDH1 gene methylation in human breast cancer accumulated. Therefore, we review the available evidence for and against the role of DNA methylation of the CDH1 gene in human breast cancer and discuss in detail the methodological reasons for conflicting results, which are of general importance for the analysis of aberrant DNA methylation in human cancer specimens. Since the loss of E-cadherin protein expression is a hallmark of invasive lobular breast cancer (ILBC), special attention is paid to CDH1 gene methylation as a potential mechanism for loss of expression in this special subtype of human breast cancer. Proper understanding of the methodological basis is of utmost importance for the correct interpretation of results supposed to demonstrate the presence and clinical relevance of aberrant DNA methylation in cancer specimens.

TERT distal promoter GC islands are critical for telomerase and together with DNMT3B silencing may serve as a senescence-inducing agent in gliomas

Telomerase is reactivated in the majority of cancers. For instance, in gliomas, it is common that the TERT promoter is mutated. Research on telomere promoter GC islands have been focused primarily on proximal TERT promoter but little is known about the distal promoter. Therefore, in this study, we investigated the proximal and distal TERT promoter, in terms of DNA methylation. We did bisulfite sequencing in zebrafish tissue samples for the distal tert promoter. In the zebrafish brain tissues, we identified a hypomethylation site in the tert promoter, and found that this hypomethylation was associated with aging and shortened telomeres. Through site directed mutagenesis in glioma cell lines, we changed 10 GC spots individually, cloned into a reporter vector, and measured promoter activity. Finally, we silenced DNMT3B and measured telomerase activity along with vidaza and adriamycin treatments. Site directed mutagenesis of glioma cell lines revealed that each of the 10 GC spots are critical for telomerase activity. Changing GC to AT abolished promoter activity in all spots when transfected into glioma cell lines. Then, through silencing of DNMT3B, we observed a reduction in hTERT expression levels, while hTR remained the same, and a major increase in senescence-associated beta-galactosidase activity. Finally, we propose a model regarding the efficacy of two chemotherapeutic drugs, adriamycin and azacytidine, on gliomas. Here, we show that distal TERT promoter is critical; changing even one GC to AT abolishes TERT promoter activity. DNMT3B, a de novo methyltransferase, together with GC islands in distal TERT promoter plays an important role in regulation of telomerase expression and senescence.

The potential of DNA methylation as a biomarker for obesity and smoking

DNA methylation is an epigenetic modification that has consistently been shown to be linked with a variety of human traits and diseases. Because DNA methylation is dynamic and potentially reversible in nature and can reflect environmental exposures and predict the onset of diseases, it has piqued interest as a potential disease biomarker. DNA methylation patterns are more stable than transcriptomic or proteomic patterns, and they are relatively easy to measure to track exposure to different environments and risk factors. Importantly, technologies for DNA methylation quantification have become increasingly cost effective-accelerating new research in the field-and have enabled the development of novel DNA methylation biomarkers. Quite a few DNA methylation-based predictors for a number of traits and diseases already exist. Such predictors show potential for being more accurate than self-reported or measured phenotypes (such as smoking behavior and body mass index) and may even hold potential for applications in clinics. In this review, we will first discuss the advantages and challenges of DNA methylation biomarkers in general. We will then review the current state and future potential of DNA methylation biomarkers in two human traits that show rather consistent alterations in methylome-obesity and smoking. Lastly, we will briefly speculate about the future prospects of DNA methylation biomarkers, and possible ways to achieve them.

Evolutionary fates of gene-body methylation and its divergent association with gene expression in pigeonpea

Pigeonpea (Cajanus cajan L. Huth) is an agronomically important legume cultivated worldwide. In this study, we extensively analyzed gene-body methylation (GbM) patterns in pigeonpea. We found a bimodal distribution of CG and CHG methylation patterns. GbM features- slow evolution rate and increased length remained conserved. Genes with moderate CG body methylation showed highest expression where as highly-methylated genes showed lowest expression. Transposable element (TE)-related genes were methylated in multiple contexts and hence classified as C-methylated genes. A low expression among C-methylated genes was associated with transposons insertion in gene-body and upstream regulatory regions. The CG methylation patterns were found to be conserved in orthologs compared with non-CG methylation. By comparing methylation patterns between differentially methylated regions (DMRs) of the three genotypes, we found that variably methylated marks are less likely to target evolutionary conserved sequences. Finally, our analysis showed enrichment of nitrogen-related genes in GbM orthologs of legumes, which could be promising candidates for generating epialleles for crop improvement.

Molecular basis of epigenetic regulation in cancer diagnosis and treatment

The global cancer cases and mortality rates are increasing and demand efficient biomarkers for accurate screening, detection, diagnosis, and prognosis. Recent studies have demonstrated that variations in epigenetic mechanisms like aberrant promoter methylation, altered histone modification and mutations in ATP-dependent chromatin remodelling complexes play an important role in the development of carcinogenic events. However, the influence of other epigenetic alterations in various cancers was confirmed with evolving research and the emergence of high throughput technologies. Therefore, alterations in epigenetic marks may have clinical utility as potential biomarkers for early cancer detection and diagnosis. In this review, an outline of the key epigenetic mechanism(s), and their deregulation in cancer etiology have been discussed to decipher the future prospects in cancer therapeutics including precision medicine. Also, this review attempts to highlight the gaps in epigenetic drug development with emphasis on integrative analysis of epigenetic biomarkers to establish minimally non-invasive biomarkers with clinical applications.

Multi-omics assessment of dilated cardiomyopathy using non-negative matrix factorization

Dilated cardiomyopathy (DCM), a myocardial disease, is heterogeneous and often results in heart failure and sudden cardiac death. Unavailability of cardiac tissue has hindered the comprehensive exploration of gene regulatory networks and nodal players in DCM. In this study, we carried out integrated analysis of transcriptome and methylome data using non-negative matrix factorization from a cohort of DCM patients to uncover underlying latent factors and covarying features between whole-transcriptome and epigenome omics datasets from tissue biopsies of living patients. DNA methylation data from Infinium HM450 and mRNA Illumina sequencing of n = 33 DCM and n = 24 control probands were filtered, analyzed and used as input for matrix factorization using R NMF package. Mann-Whitney U test showed 4 out of 5 latent factors are significantly different between DCM and control probands (P<0.05). Characterization of top 10% features driving each latent factor showed a significant enrichment of biological processes known to be involved in DCM pathogenesis, including immune response (P = 3.97E-21), nucleic acid binding (P = 1.42E-18), extracellular matrix (P = 9.23E-14) and myofibrillar structure (P = 8.46E-12). Correlation network analysis revealed interaction of important sarcomeric genes like Nebulin, Tropomyosin alpha-3 and ERC-protein 2 with CpG methylation of ATPase Phospholipid Transporting 11A0, Solute Carrier Family 12 Member 7 and Leucine Rich Repeat Containing 14B, all with significant P values associated with correlation coefficients >0.7. Using matrix factorization, multi-omics data derived from human tissue samples can be integrated and novel interactions can be identified. Hypothesis generating nature of such analysis could help to better understand the pathophysiology of complex traits such as DCM.

Integrated multi-omics analyses reveal that BCAM is associated with epigenetic modification and tumor microenvironment subtypes of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common and highly heterogeneous subtype of renal cell carcinoma. Dysregulated basal cell adhesion molecule (BCAM) gene is associated with poor prognosis in various cancers. However, the dysregulated functions and related multi-omics features of BCAM in ccRCC stay unclear.

RESULTS

BCAM expression was aberrantly downregulated in ccRCC and correlated with adverse pathological parameters and poor prognosis. Low mRNA expression of BCAM was remarkably associated with its CpG methylation levels and BAP1 mutation status. Patients with lower-expressed BCAM concomitant with BAP1 mutation had a worse prognosis. Using RNA-seq data from The cancer genome atlas, we found that compared to the BCAM-high expression subgroup, ccRCC patients in the BCAM-low expression subgroup had significantly higher levels of immune infiltration, higher immune checkpoint expression levels and lower TIDE (tumor immune dysfunction and exclusion) score, indicating potential better response to immunotherapy. Data from the Clinical Proteomic Tumor Analysis Consortium further validated the association between low BCAM expression and CD8 + inflamed phenotype at protein level. Meanwhile, our results suggested that the angiogenesis-related pathways were enriched in the BCAM-high expression subgroup. More importantly, according to the data from the GDSC database, we revealed that the BCAM-high expression subgroup should be more sensitive to anti-angiogenetic therapies, including sorafenib, pazopanib and axitinib.

CONCLUSIONS

These results suggest that BCAM could serve as a biomarker distinguishing different tumor microenvironment phenotypes, predicting prognosis and helping therapeutic decision-making for patients with ccRCC.

SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions

MOTIVATION

Aberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factor's motif.

RESULTS

SEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions for CTCF. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease.

AVAILABILITY AND IMPLEMENTATION

SEMplMe is available from https://github.com/Boyle-Lab/SEMplMe .

Large-scale transcriptomic analysis of coding and non-coding pathological biomarkers, associated with the tumor immune microenvironment of thyroid cancer and potential target therapy exploration

Papillary thyroid carcinoma (PTC) is the most prevalent endocrine malignancy with a steadily increasing global incidence in recent decades. The pathogenesis of PTC is poorly understood, and the present diagnostic protocols are deficient. Thus, identifying novel prognostic biomarkers to improve our understanding of the mechanisms of pathogenesis, diagnosis, and designing therapeutic strategies for PTC is crucial. In this study, we integrated 27 PTC transcriptomic datasets and identified overlapping differentially expressed genes (DEGs) and differentially expressed microRNAs, collectively known as thyroid tumor-enriched proteins (TTEPs), and TTEmiRs, respectively. Our integrated bioinformatics analysis revealed that TTEPs were associated with tumor stages, poor surgical outcomes, distant metastasis, and worse prognoses in PTC cohorts. In addition, TTEPs were found to be associated with tumor immune infiltrating cells and immunosuppressive phenotypes of PTC. Enrichment analysis suggested the association of TTEPs with epithelial-to-mesenchymal transition (EMT), cell-matrix remodeling, and transcriptional dysregulation, while the TTEmiRs (miR-146b-5p and miR-21-5p) were associated with the modulation of the immune response, EMT, migration, cellular proliferation, and stemness. Molecular docking simulations were performed to evaluate binding affinities between TTEPs and antrocinnamomin, antcin, and antrocin, the bioactive compounds from one of the most reputable Taiwan indigenous medicinal plants (Antrodia camphorata). Our results revealed that antcin exhibited higher binding efficacies toward FN1, ETV5, and NRCAM, whereas antrocin demonstrated the least. Among the targets, fibronectin (FN1) demonstrated high ligandability potential for the compounds whereas NRCAM demonstrated the least. Collectively, our results hinted at the potential of antcin for targeting TTEPs. In conclusion, this comprehensive bioinformatics analysis strongly suggested that TTEPs and TTEmiRs could be used as potential diagnostic biomarker signatures and be exploited as potential targets for therapeutics development.

Prenatal vitamin intake in first month of pregnancy and DNA methylation in cord blood and placenta in two prospective cohorts

BACKGROUND

Prenatal vitamin use is recommended before and during pregnancies for normal fetal development. Prenatal vitamins do not have a standard formulation, but many contain calcium, folic acid, iodine, iron, omega-3 fatty acids, zinc, and vitamins A, B6, B12, and D, and usually they contain higher concentrations of folic acid and iron than regular multivitamins in the US Nutrient levels can impact epigenetic factors such as DNA methylation, but relationships between maternal prenatal vitamin use and DNA methylation have been relatively understudied. We examined use of prenatal vitamins in the first month of pregnancy in relation to cord blood and placenta DNA methylation in two prospective pregnancy cohorts: the Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk Learning Early Signs (MARBLES) studies.

RESULTS

In placenta, prenatal vitamin intake was marginally associated with -0.52% (95% CI -1.04, 0.01) lower mean array-wide DNA methylation in EARLI, and associated with -0.60% (-1.08, -0.13) lower mean array-wide DNA methylation in MARBLES. There was little consistency in the associations between prenatal vitamin intake and single DNA methylation site effect estimates across cohorts and tissues, with only a few overlapping sites with correlated effect estimates. However, the single DNA methylation sites with p-value < 0.01 (EARLI cord nCpGs = 4068, EARLI placenta nCpGs = 3647, MARBLES cord nCpGs = 4068, MARBLES placenta nCpGs = 9563) were consistently enriched in neuronal developmental pathways.

CONCLUSIONS

Together, our findings suggest that prenatal vitamin intake in the first month of pregnancy may be related to lower placental global DNA methylation and related to DNA methylation in brain-related pathways in both placenta and cord blood.

YAP induces an oncogenic transcriptional program through TET1-mediated epigenetic remodeling in liver growth and tumorigenesis

Epigenetic remodeling is essential for oncogene-induced cellular transformation and malignancy. In contrast to histone post-translational modifications, how DNA methylation is remodeled by oncogenic signaling remains poorly understood. The oncoprotein YAP, a coactivator of the TEAD transcription factors mediating Hippo signaling, is widely activated in human cancers. Here, we identify the 5-methylcytosine dioxygenase TET1 as a direct YAP target and a master regulator that coordinates the genome-wide epigenetic and transcriptional reprogramming of YAP target genes in the liver. YAP activation induces the expression of TET1, which physically interacts with TEAD to cause regional DNA demethylation, histone H3K27 acetylation and chromatin opening in YAP target genes to facilitate transcriptional activation. Loss of TET1 not only reverses YAP-induced epigenetic and transcriptional changes but also suppresses YAP-induced hepatomegaly and tumorigenesis. These findings exemplify how oncogenic signaling regulates the site specificity of DNA demethylation to promote tumorigenesis and implicate TET1 as a potential target for modulating YAP signaling in physiology and disease.

Molecular Mechanisms of Epigenetic Regulation, Inflammation, and Cell Death in ADPKD

Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder, which is caused by mutations in the PKD1 and PKD2 genes, characterizing by progressive growth of multiple cysts in the kidneys, eventually leading to end-stage kidney disease (ESKD) and requiring renal replacement therapy. In addition, studies indicate that disease progression is as a result of a combination of factors. Understanding the molecular mechanisms, therefore, should facilitate the development of precise therapeutic strategies for ADPKD treatment. The roles of epigenetic modulation, interstitial inflammation, and regulated cell death have recently become the focuses in ADPKD. Different epigenetic regulators, and the presence of inflammatory markers detectable even before cyst growth, have been linked to cyst progression. Moreover, the infiltration of inflammatory cells, such as macrophages and T cells, have been associated with cyst growth and deteriorating renal function in humans and PKD animal models. There is evidence supporting a direct role of the PKD gene mutations to the regulation of epigenetic mechanisms and inflammatory response in ADPKD. In addition, the role of regulated cell death, including apoptosis, autophagy and ferroptosis, have been investigated in ADPKD. However, there is no consensus whether cell death promotes or delays cyst growth in ADPKD. It is therefore necessary to develop an interactive picture between PKD gene mutations, the epigenome, inflammation, and cell death to understand why inherited PKD gene mutations in patients may result in the dysregulation of these processes that increase the progression of renal cyst formation.

Role of Transposable Elements in Genome Stability: Implications for Health and Disease

Most living organisms have in their genome a sizable proportion of DNA sequences capable of mobilization; these sequences are commonly referred to as transposons, transposable elements (TEs), or jumping genes. Although long thought to have no biological significance, advances in DNA sequencing and analytical technologies have enabled precise characterization of TEs and confirmed their ubiquitous presence across all forms of life. These findings have ignited intense debates over their biological significance. The available evidence now supports the notion that TEs exert major influence over many biological aspects of organismal life. Transposable elements contribute significantly to the evolution of the genome by giving rise to genetic variations in both active and passive modes. Due to their intrinsic nature of mobility within the genome, TEs primarily cause gene disruption and large-scale genomic alterations including inversions, deletions, and duplications. Besides genomic instability, growing evidence also points to many physiologically important functions of TEs, such as gene regulation through cis-acting control elements and modulation of the transcriptome through epigenetic control. In this review, we discuss the latest evidence demonstrating the impact of TEs on genome stability and the underling mechanisms, including those developed to mitigate the deleterious impact of TEs on genomic stability and human health. We have also highlighted the potential therapeutic application of TEs.

Comprehensive Pan-Cancer Analysis of Senescence With Cancer Prognosis and Immunotherapy

Senescence is a double-edged sword in tumorigenesis and affects the immunotherapy response through the modulation of the host’s immune system. However, there is currently a lack of comprehensive analysis of the senescence-related genes (SRGs) in human cancers, and the predictive role of senescence in cancer immunotherapy response has not been explored. The multi-omics approaches were performed in this article to conduct a systematic pan-cancer genomic analysis of SRGs in cancer. In addition, we calculated the generic senescence score (SS) to quantify the senescence levels in cancers and explored the correlations of SS with cancer prognosis, biological processes, and tumor microenvironment (TME). The gene signatures were deregulated in multiple cancers and indicated a context-dependent correlation with prognosis, tumor-immune evasion, and response to therapy across various tumor types. Further analysis disclosed that SS was positively associated with the infiltration levels of immune suppressive cells, including induced Tregs (iTregs), central memory Ts (Tcms), and natural Tregs (nTregs), and negatively associated with immune killer cells, including natural killers (NKs) and mucosal-associated invariant Ts (MAITs). Moreover, the SS was significantly correlated with tumor-associated macrophages (TAMs), cancer-associated fibroblasts (CAFs), immune-related genes, and immune checkpoints and had a predictive value of immunotherapy response. Thus, the expression of SRGs was involved in resistance to several anticancer drugs. Our work illustrates the characterization of senescence across various malignancies and highlights the potential of senescence as a biomarker of the response to immunotherapy.

Comparison of DNA methylation measurements from EPIC BeadChip and SeqCap targeted bisulphite sequencing in PON1 and nine additional candidate genes

Epigenome-wide association studies (EWAS) are widely implemented in epidemiology, and the Illumina HumanMethylationEPIC BeadChip (EPIC) DNA microarray is the most-used technology. Recently, next-generation sequencing (NGS)-based methods, which assess DNA methylation at single-base resolution, have become more affordable and technically feasible. While the content of microarray technology is fixed, NGS-based approaches, such as the Roche Nimblegen, SeqCap Epi Enrichment System (SeqCap), offer the flexibility of targeting most CpGs in a gene. With the current usage of microarrays and emerging NGS-based technologies, it is important to establish whether data generated from the two platforms are comparable. We harnessed 112 samples from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) birth cohort study and compared DNA methylation between the EPIC microarray and SeqCap for PON1 and nine additional candidate genes, by evaluating epigenomic coverage and correlations. We conducted multivariable linear regression and principal component analyses to assess the ability of the EPIC array and SeqCap to detect biological differences in gene methylation by the PON1_-108 single nucleotide polymorphism. We found an overall high concordance (r = 0.84) between SeqCap and EPIC DNA methylation, among highly methylated and minimally methylated regions. However, substantial disagreement was present between the two methods in moderately methylated regions, with SeqCap measurements exhibiting greater within-site variation. Additionally, SeqCap did not capture PON1 SNP associated differences in DNA methylation that were evident with the EPIC array. Our findings indicate that microarrays perform well for analysing DNA methylation in large cohort studies but with limited coverage.

ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences

Epigenetic modifications have a vital role in gene expression and are linked to cellular processes such as differentiation, development, and tumorigenesis. Thus, the availability of reliable and accurate methods for identifying and defining these changes facilitates greater insights into the regulatory mechanisms that rely on epigenetic modifications. The current experimental methods provide a genome-wide identification of epigenetic modifications; however, they are expensive and time-consuming. To date, several machine learning methods have been proposed for identifying modifications such as DNA N6-Methyladenine (6mA), RNA N6-Methyladenosine (m6A), DNA N4-methylcytosine (4mC), and RNA pseudouridine ( Ψ). However, these methods are task-specific computational tools and require different encoding representations of DNA/RNA sequences. In this study, we propose a unified deep learning model, called ZayyuNet, for the identification of various epigenetic modifications. The proposed model is based on an architecture called, SpinalNet, inspired by the human somatosensory system that can efficiently receive large inputs and achieve better performance. The proposed model has been evaluated on various epigenetic modifications such as 6mA, m6A, 4mC, and Ψ and the results achieved outperform current state-of-the-art models. A user-friendly web server has been built and made freely available at http://nsclbio.jbnu.ac.kr/tools/ZayyuNet/.

Liquid biopsies to predict CDK4/6 inhibitor efficacy and resistance in breast cancer

Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors combined with endocrine therapy have transformed the treatment of estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer. However, some patients do not respond to this treatment, and patients inevitably develop resistance, such that novel biomarkers are needed to predict primary resistance, monitor treatment response for acquired resistance, and personalize treatment strategies. Circumventing the spatial and temporal limitations of tissue biopsy, newly developed liquid biopsy approaches have the potential to uncover biomarkers that can predict CDK4/6 inhibitor efficacy and resistance in breast cancer patients through a simple blood test. Studies on circulating tumor DNA (ctDNA)-based liquid biopsy biomarkers of CDK4/6 inhibitor resistance have focused primarily on genomic alterations and have failed thus far to identify clear and clinically validated predictive biomarkers, but emerging epigenetic ctDNA methodologies hold promise for further discovery. The present review outlines recent advances and future directions in ctDNA-based biomarkers of CDK4/6 inhibitor treatment response.

SOX5 promotes cell growth and migration through modulating the DNMT1/p21 pathway in bladder cancer

Bladder cancer (BC) is one of the most prevalent and life-threatening cancers among the male population worldwide. Sex determining region Y-box protein 5 (SOX5) plays important roles in a variety of human cancers. However, little research has been conducted on the function and underlying mechanism of SOX5 in BC. In the present study, we first reveal the increased expression of SOX5 in BC tissues and in vitro cells lines. Second, we discover that inhibition of SOX5 inhibits cell growth and migration but promotes cell apoptosis. Meanwhile, ectopic SOX5 expression stimulates cell growth and migration in BC cells. Then, we show that suppressing SOX5 inhibits the expression of DNA methyltransferase 1 (DNMT1), and that overexpressing DNMT1 alleviates the cell progress of BC cells inhibited by SOX5. Furthermore, we demonstrate that DNMT1 inhibits p21 expression by affecting DNA methylation of the p21 promoter. Collectively, we demonstrate that SOX5 exerts its functions in BC cells by modulating the SOX5/DNMT1/p21 pathway. Finally, we demonstrate that SOX5 knockdown inhibits xenograft tumor growth in vivo. In conclusion, our study elucidates the oncogenic role of SOX5 and its underlying molecular mechanism in BC, and reveals a novel pathway which has the potential to serve as a diagnostic biomarker and therapeutic target for BC.

Dynamic changes in hepatic DNA methylation during the development of nonalcoholic fatty liver disease induced by a high-sugar diet

DNA methylation is an important epigenetic mechanism of gene expression control. The present study aimed to evaluate the temporal effect of isocaloric high-sugar diet (HSD) intake on the development of nonalcoholic fatty liver disease (NAFLD) and the role of DNA methylation in this event. Newly weaned Wistar rats were divided into eight groups and fed a standard chow diet or an HSD ad libitum for 4 weeks, 8 weeks, 15 weeks, and 18 weeks. After the experimental periods, the animals were euthanized and their livers were removed for histological analysis, gene expression of maintenance methylase (Dnmt1), de novo methylases (Dnmt3a and Dnmt3b), demethylases (Tet2 and Tet3) of DNA, and global DNA methylation. HSD intake led to the gradual development of NAFLD. HSD intake for 18 weeks was associated with downregulation of Dnmt1 expression and global DNA hypomethylation; these results were negatively correlated with more severe steatosis scores observed in these animals. The HSD consumption for 18 weeks was also associated with a decrease in Dnmt3a and Tet2 expression. Interestingly, the expression of de novo methyltransferase Dnmt3b was reduced by HSD during all experimental periods. Together, these results indicate that the downregulation of de novo DNA methylation, Dnmt3b, induced by HSD is the primary factor in the development of NAFLD. On the other hand, disease progression is associated with downregulation of maintenance DNA methylation and global DNA hypomethylation. These results suggest a link between the dynamic changes in hepatic DNA methylation and the development of NAFLD induced by an HSD intake.

Rapid and ultrasensitive electrochemical detection of DNA methylation for ovarian cancer diagnosis

Alterations in DNA methylation, a stable epigenetic marker, are important components in the development of cancer. It is vital to develop diagnostic systems with the ability to rapidly quantify DNA methylation with high sensitivity and selectivity. However, the analysis of DNA methylation must address two main challenges: (i) ultralow abundance and (ii) differentiating methylated cytosine from normal cytosine on target DNA sequence in the presence of an overwhelming background of circulating cell-free DNA. Here we report the development of an ultrasensitive and highly-selective electrochemical biosensor for the rapid detection of DNA methylation in blood. The sensing of DNA methylation involves the hybridization on a network of probe DNA modified gold-coated magnetic nanoparticles (DNA-Au@MNPs) complementary to target DNA, and subsequently enzymatic cleavage to differentiate methylated DNA strands from corresponding unmethylated DNA strands. The biosensor presents a dynamic range from 2 aM to 20 nM for 110 nucleotide DNA sequences containing a single-site methylation with the lowest detected concentration of 2 aM. This DNA-Au@MNPs based sensor provides a promising method to achieve 35 min response time and minimally invasive diagnosis of ovarian cancer.

Epigenetic DNA Methylation Signatures Associated With the Severity of Paget's Disease of Bone

Background: Paget's disease of bone (PDB) is characterized by focal areas of dysregulated bone turnover resulting in increased bone loss and abnormal bone formation with variable severity. PDB has a complex etiology and both genetics and environmental factors have been implicated. A recent study has identified many differentially methylated loci in PDB compared to healthy subjects. However, associations between DNA methylation profiles and disease severity of PDB have not been investigated. Objectives: To investigate the association between DNA methylation signals and PDB severity. Methods: Using 232 well-characterized PDB subjects from the PRISM trial, a disease severity score was devised based on the clinical features of PDB. DNA methylation profiling was performed using Illumina Infinium HumanMethylation 450K array. Results: We identified 100 CpG methylation sites significantly associated with PDB severity at FDR <0.05. Additionally, methylation profiles in 11 regions showed Bonferroni-significant association with disease severity including six islands (located in VCL, TBX5, CASZ1, ULBP2, NUDT15 and SQSTM1), two gene bodies (CXCR6 and DENND1A), and 3 promoter regions (RPL27, LINC00301 and VPS29). Moreover, FDR-significant effects from region analysis implicated genes with genetic variants previously associated with PDB severity, including RIN3 and CSF1. A multivariate predictor model featuring the top severity-associated CpG sites revealed a significant correlation (R = 0.71, p = 6.9 × 10-16) between observed and predicted PDB severity scores. On dichotomizing the severity scores into low and high severity, the model featured an area under curve (AUC) of 0.80, a sensitivity of 0.74 and a specificity of 0.68. Conclusion: We identified several CpG methylation markers that are associated with PDB severity in this pioneering study while also highlighting the novel molecular pathways associated with disease progression. Further work is warranted to affirm the suitability of our model to predict the severity of PDB in newly diagnosed patients or patients with family history of PDB.

Analysis of the long-read sequencing data using computational tools confirms the presence of 5-methylcytosine in the Saccharomyces cerevisiae genome

Modification of DNA bases plays important roles in the epigenetic regulation of eukaryotic gene expression. Among the different types of DNA methylation, 5-methylcytosine (5mC) is common in higher eukaryotes. Although bisulfite sequencing is the established detection method for this modification, newer methods, such as Oxford nanopore sequencing, have been developed as quick and reliable alternatives. An earlier study using sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) indicated the presence of 5mC at very low concentration in Saccharomyces cerevisiae. More recently, a comprehensive study of the yeast genome found 40 5mC sites using the computational tool Nanopolish on nanopore sequencing output raw data. In the present study, we are trying to validate the prediction of the 5mC modifications in yeast with Nanopolish and two other nanopore software tools, Tombo and DeepSignal. Using publicly available genome sequencing data, we compared the open-access computational tools, including Tombo, Nanopolish and DeepSignal, for predicting 5mC. Our results suggest that these tools are indeed capable of predicting DNA 5mC modifications at a specific location from Oxford nanopore sequencing data. We also predicted that 5mC present in the S. cerevisiae genome might be located predominantly at the RDN locus of chromosome 12.